Managerial
8. Analysis of the Skills Inventory before Data Reduction
8.4 The Task Descriptors
The one remaining piece of evidence that affects the whole sample is that of the task descriptors supplied by respondents in section A of the questionnaire. They were asked to identify 'major tasks in your current job code', and this section of the questionnaire precedes the more detailed Likert scales with the 35 KSAs. There is space on the
questionnaire for four keyword or phrases describing tasks in descending order of
importance. As the 35 KSAs are over the page, the intention of the design was that the respondents would have described the four tasks before having seen the KSA names.
As previously described in section 7.2 these 'task descriptors' were manually codified and classified on input. In the research design they fulfilled the purpose of adding further data about job content in terms of skills requirements. Not only have they contributed to the definition of 1 5 (as 'collapsed' sub-categories in Table 7-2) of the 35 KSAs, but further content analysis at this overview stage may help clarify the results already presented in this chapter.
The research approach adopted here is a technique within content analysis that Weber terms 'content category counts' (Weber, 1985:41 ), whereby words or phrases that have been classified into categories are counted. As he points out
... counting is based on the assumption that higher relative counts (proportions, percentages, or ranks) reflect higher concern with the category. (Weber, 1 9�5:56)
Unlike computer-generated word frequency lists and concordances which can be error prone to the problems of contextual ambiguity, category counting in this study is more manageable. The precise nature of the task descriptors and their hand-coded classification increase the strength of semantic validity.
Following the technique described above, the first part of the analysis process entailed the counting of all task descriptors classified by 72 codes (see Table 7- 1 ) which were then reduced to the original 35 KSAs (see Table 7-2). These frequency counts for each KSA are shown in Table 8-5 and appear in the 'raw score' column.
The next part of the procedure was to take into account the priority ranking implicit in the order of the descriptors as recorded on the four lines made available
�
Question 9, section A of the questionnaires. The weighting scheme can be likened to a 4-point Likert scale: 4 points for an entry on the topmost line, 3 for the next and so on down to a 1 for the fourth entry. Based on this scheme the relevant weighting multiplier ( 1 ,2,3 or 4) was applied to all raw scores to arrive at the column headed 'Ranked score' in Table8-5.
Table 8-5: Content Category Count: Business-related and Technology-related Task Descriptors
Business-related Score Technology-related Score
Raw Ranked Raw Ranked
1. Information gathering techniques 2 8 2. Systems Analysis & Design techniques 1 90 5 7 1
3.Verbal & presentation skills 4 9 8.3rd generation programming 0 0
4. Project management skills 1 33 360 9. 4th generation programming 1 45 365
5. People skills 145 373 10. DBMS & database design 23 65
6. Health & safety 0 0 1 1 . Operating Systems 2 7
7. Written communication skills 27 56 12. Mainframe systems 2 7
18. Understanding legal issues 1 3 13. Mini-computer systems 0 0
20. Statistical & simulation techniques 3 1 1 14. Telecomms & networking concepts l7 46
21. Decision support systems I 3 15. Computer security & disaster recovery 6 1 8
22. Strategic lnfo. Systems Planning 1 3 1 402 16. Use & evaluation of software packages 7 2 1
24. Knowledge of the business area 86 2 1 0 1 7 . Computer operations, JCL, data capture 7 1 7 27. M arketing skills 86 2 1 7 19. Prototyping techniques 0 0
28. Quality management concepts 72 173 23. CASE techniques 3 9
29. Project evaluation & justification 50 1 27 25. Personal computer systems 6 1 6 30. Negotiating skills 7 1 7 26. Computer controls & auditing 33 82
34. General management skills 1 3 1 379 31. Use & evaluation of hardware 3
35. Keeping abreast with new technology 9 2 1 32. Documentation writing skills 7 1 3 33. User training & support 1 57 365
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888 2369 606 1605
% 59.44 59.61 40.56 40.39
As can be seen from the summative percentages in the table, the allowance made for the priority ranking of the task descriptors had no appreciable effect on the overall
percentage difference between the business-related and technology-related categories. This is partly explained by the fact that the responses are focused into a few popular KSAs. On the technology-related side the words and phrases seem to reflect the actual workplace daily activities: 2. Systems Analysis & Design techniques (with the highest scores) 9. 4th generation programming and 33. User training & support (with the next highest raw scores). In a similar pragmatic fashion, on the business-related side s. People skills (the scores of which are similar to those of 4GL programming), 4. Project management skills, 22. Strategic Info. Systems Planning and 34. General management skills predominate - the latter two scoring high ranked scores. Closely following in importance are 'knowledge of the business area' and marketing skills.
Somewhat surprisingly, given the frequent complaint from recruitment agencies and employers, there is little overt mention of communication skills per se. It may be that the task descriptors are portraying an aspect of workplace reality which does not always surface in the more formal part of the questionnaire.
In the end, however, the total counts of both raw and ranked scores show that business related words and phrases out-numbered the technology-related by approximately 50%, as pictorially represented by the piechart in Figure 8-2 which shows the ranked descriptors (i.e. the keywords weighted by their line position on the questionnaire).
Figure 8-2: Total Number of Ranked Task Descriptors
1 605
The above procedure of conducting content and frequency analyses of keywords (task descriptors) expressed by respondents to describe the essential skills in their current jobs is designed to test whether free form textual evidence may corroborate the more precise questions relating to identified skill items. It needs to be remembered that this procedure covers written enunciations of the skills seen to be utilised in the respondents' current
positions, and so warrants comparison with the 'Now' column of means in Table 8-2.
Table 8-6 is an attempt to explore such a comparison. It is based on the top 10 KSAs extracted from Table 8-5 which have the highest ranked scores, arrived at by counting and categorising task descriptors. Their nth position in terms of their ranking is displayed in descending order within either the business-related or technology-related group. For each of these KSAs the corresponding nth ranking of the 'Now' mean from Table 8-2 is listed alongside in the first column.
Table 8-6: Current Job KSAs: Comparing the Rankings of Means and Task Descriptor Ranked Scores
Business-related
22. Strategic Info. Systems Planning 34. General management skills
5. People skills
4. Project management skills 27. M arketing skills
24. Knowledge of the business area
28. Quality management concepts 29. Project evaluation & justification
Rank # Now Ranked Mean Score 1 8 2 9 3 1 4 8 6 1 5 7 5 8 1 2 9 1 1 1 0 Technology-related Rank # Now Ranked Mean Score
2. Systems Analysis & Design techniques 20
9. 4th generation programming 27 5=
33. User training & support 1 7 5=
An initial inspection reveals what seems to be a discordance between the respondents' textual and their Likert scale accounts of two of the job skills. According to this evidence respondents are much more likely to write that their current jobs involve strategic IS planning on the business side and systems analysis and design techniques in
the more technical arena. The same two KSAs' means on the Likert scale ranked in the mid-range of 1 8th and 20th. A closer inspection, however, shows that of the 8 business related KSAs that ranked highly in the textual account 6 also are ranked within the top
1 2 'Now' means. A general observation has to be that the sample is once again reinforcing the need for more business-related skills in their current workplaces
The results in this chapter have clearly demonstrated that the skills inventory for IS personnel in New Zealand is perceived by IS practitioners to have undergone significant change. IS skills in both categories of technical and business are perceived to have increased in importance. Moreover it seems clear that while the profession still sees a need for no fewer technical skills, it rates the importance of organisational/business skills as exceeding former requirements. The overall impression created by the results so far is a skewness towards more increase in the value placed on business-related skills relative to those that are technology-related.
This chapter has answered in the affirmative the first of the three research questions posed at the end of Chapter 2, namely:
• are organisational/managerial skills becoming more important for IS professionals in
their jobs?
It has also explored in some detail the third research question:
• what are the particular skills required for an IS professional in New Zealand?
This chapter has considered the sample of respondents as a whole, and has retained a holistic view. The next chapter moves from the general to the more specific viewpoint of managers in the IS profession. They represent a large proportion of the sample. They have elected to be members of the profession and so probably started their careers in the technical sphere before making the transition to managerial positions that require a different emphasis in the skills inventory. Their perceptions concerning the contents of that inventory will be explored next.